Revision 8bc91fa72139cef5f479dd9fb9e6db9162ca3b93 (click the page title to view the current version)
AIS2204 Maskinsyn
- See Lecture Notes for learning materials
- See Blackboard for announcements and discussion boards.
Practical Information
- There are no compulsory exercises. It is your responsibility to the exercises you need to do to understand the subject and gain experience.
- Feedback is provided in class upon demonstration of own work and solutions.
- The module emphasises the relation between theoretical and practical understanding.
How to work with the module
- Read the theory.
- Do practical exercises to test your theoretical understanding
- Evaluate your own solutions and reflect upon
- what have you learnt from the exercise?
- what do you yet not know?
- Don’t do a lot of exercises quickly. It is better to make sure that you comprehend a few exercises fully, and can justify and validate your own reasoning.
- Ask Questions.
I will generally not repeat material unsolicited, but I am very happy to discuss any question you may have. - Keep a diary. Make sure you can refer back to previous ideas and reuse previous solutions.
The practical exercises
The practical exercises are designed to give both
- standalone prototypes 3-5 times during the semester, each demonstrating key aspects of the theory.
- combine together into a final machine vision system, rudimentary but complete.
How does the exam work
- Oral Exam.
- You get seven minutes to demonstrate the highlights of your understanding of the subject. Make a case for the grade you think you deserve.
- The examiner will use the rest of the time for questions to clarify and to demonstrate expected breadth and depth.
- Note that there are both theoretical and practical learning outcomes, and the module emphasises the relation between these two.
- Capacity: 30 candidates
- Assessment Guide
Syllabus
- From [Ma (2005): An Invitation to 3-D Vision: From Images to Geometric Models] (https://bibsys-almaprimo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_cdi_askewsholts_vlebooks_9780387217796&context=PC&vid=NTNU_UB&lang=no_NO&search_scope=default_scope&adaptor=primo_central_multiple_fe&tab=default_tab&query=any,contains,ma%20invitation%203d%20vision&offset=0)
- Chapters 1-6 and 11
- All lectures and exercises
- Additional reading:
- Ma 2004, Chapters 7-10 and 12.
- OpenCV 3 Computer Vision with Python Cookbook by Alexey Spizhevoy (author) from O’Reilly can be a useful supplement. Search for it in Oria. There is an e-book available.